PD6646 Sample Summary

## `summarise()` has grouped output by 'patient', 'age_at_sample_exact', 'age_at_sample', 'DOB', 'DATE_OF_DIAGNOSIS'. You can override using the `.groups` argument.
## Joining, by = "PDID"
patient ID age_at_sample_exact cell_type phase BaitLabel
3 PD6646 PD6646n 76.44353 PB Gran Recapture PD6646n
4 PD6646 PD6646o 78.97331 PB Gran Recapture PD6646o
5 PD6646 PD6646p 80.14237 PB Gran Recapture PD6646p
1 PD6646 COLONY81 81.01027 BFU-E-Colony Colony NA
6 PD6646 PD6646q 82.97878 PB Gran Recapture PD6646q
2 PD6646 COLONY85 84.70089 BFU-E-Colony Colony NA

Tree

tree=plot_basic_tree(PD$pdx,label = PD$patient,style="classic")

Expanded Tree with Node Labels

The nodes in this plot can be cross-referenced with nodes specified in subsequent results. The plot also serves to give an idea of what the topology at the top of the tree looks like.

tree=plot_basic_tree(expand_short_branches(PD$pdx,prop = 0.1),label = PD$patient,style="classic")
node_labels(tree)

Timing of driver mutations (using Model = poisson_tree )

Note that the different colours on the tree indicate the separately fitted mutation rate clades.

Driver Specific Mutation Rates & Telomere Lengths by Colony & Timepoint

## 
## Random-Effects Model (k = 1; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc 
##   0.0000   -0.0000    4.0000      -Inf   16.0000   
## 
## tau^2 (estimated amount of total heterogeneity): 0
## tau (square root of estimated tau^2 value):      0
## I^2 (total heterogeneity / total variability):   0.00%
## H^2 (total variability / sampling variability):  1.00
## 
## Test for Heterogeneity:
## Q(df = 0) = 0.0000, p-val = 1.0000
## 
## Model Results:
## 
## estimate      se     zval    pval    ci.lb    ci.ub 
##  19.3909  0.6033  32.1417  <.0001  18.2085  20.5734  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'patient'. You can override using the `.groups` argument.
node driver status child_count type colony_count mean_lambda_rescaled correction sd_rescaled lb_rescaled ub_rescaled median_rescaled p_lt_wt
-1 WT 1 -1 local 18 19.39092 1.014996 0.3639650 18.69665 20.12276 19.38593 NA
121 DNMT3A 1 99 local 8 18.68510 1.014996 0.4727588 17.79205 19.65477 18.67391 0.870800
142 JAK2:DNMT3A 1 77 local 73 22.60973 1.014996 1.5523421 19.71770 25.75073 22.56640 0.016100
175 9pUPD:JAK2:DNMT3A 0 3 local 3 25.39854 1.014996 1.9432401 21.78597 29.39981 25.33098 0.000375
27 9pUPD:JAK2:DNMT3A 0 1 local 1 21.37484 1.014996 3.8666001 12.74849 28.33233 21.68363 0.266800
124 CBL:DNMT3A 1 14 local 14 18.26586 1.014996 0.7048151 16.92716 19.71524 18.24567 0.914675

Driver Acquisition Timeline

All ages are in terms of post conception years. The vertical red lines denote when colonies were sampled and blue lines when targeted follow up samples were taken.

patient node driver child_count lower_median upper_median lower_lb95 lower_ub95 upper_lb95 upper_ub95 N group age_at_diagnosis_pcy max_age_at_sample min_age_at_sample
PD6646 121 DNMT3A 99 0.0110787 27.17183 0.0082774 0.0254408 24.99919 29.40281 6 DNMT3A 76.80767 85.42916 77.1718
PD6646 124 CBL 14 32.1642463 50.72960 29.9563203 34.4032654 48.41968 52.95501 6 CBL 76.80767 85.42916 77.1718
PD6646 142 JAK2 77 29.6007868 63.17088 27.4336204 31.8099078 60.35690 65.61309 6 JAK2 76.80767 85.42916 77.1718
PD6646 175 9pUPD 3 67.3874939 72.79130 65.1055774 69.3451450 71.02458 74.30215 6 9pUPD 76.80767 85.42916 77.1718

Copy Number Variation and Timing

Summary of LOH timing inference

## Timings using the Clade Specific Rates
label node het.sensitivity chr start end nhet nhom mean_loh_event lower_loh_event upper_loh_event t_before_end t_before_end_lower t_before_end_upper kb count_in_bin count_se pmut pmut_se xmean xse_mean xsd x2.5. x50. x97.5. xn_eff xRhat lmean lse_mean patient driver3 child_count
9pUPD_A 175 0.9629 9 10469 5464376 0 0 70.26 67.53 72.64 2.497 0.1131 5.23 5400000 838 28.95 0.00183 6.322e-05 0.5387 0.002153 0.2867 0.0336 0.5591 0.9791 17730 1 1.000 4.126e-07 PD6646 9pUPD:JAK2:DNMT3A 3
9pUPD_B 27 0.7240 9 10469 33800406 1 2 NA NA NA NA NA NA 33800000 6732 82.05 0.01470 1.792e-04 0.6540 0.001191 0.1897 0.2448 0.6774 0.9478 25378 1 6.447 4.901e-04 NA NA NA

Duplications?

VAF Distribution of Targeted Follow Up Samples

Here we exclude all local CNAs and depict as color VAF plots